Breast cancer diagnosis may be improved by optical fluorescence imaging techniques in the near-infrared wavelength range. We have shown that the recently proposed space-space MUSIC (multiple signal classification) algorithm allows the 3-D localization of focal fluorophore-tagged lesions in a turbid medium from 2-D fluorescence data obtained from laser excitations at different positions. The data are assumed to be measured with two parallel planar sensor arrays on the top and bottom of the medium. The laser sources are integrated at different positions in one of the planes. The space-space data are arranged into an M×N matrix (M, number of sensors; N, number of excitation sources). A singular-value decomposition (SVD) of this matrix yields the detectable number of spot regions with linearly independent behavior with respect to the laser excitation positions and thus allows definition of a signal subspace. Matches between this signal subspace and data from model spots are tested at scanned points in a model medium viewed as the breast region under study. The locations of best matches are then considered the centers of gravity of focal lesions. The optical model used was unbounded and optically homogeneous. Nevertheless, simulated spots in bounded, inhomogeneous media modeling the breast could be localized accurately.